January Seminar: Jeff Leek, PhD - Building and using AI engines – what do we do when we’ve machine learned everything?
Thursday, January 15, 2026
12-1 p.m
Hybrid: In-person at Mission Hall, MH-1406 or Zoom Register here
An AI engine is a system where one collects data from a system, the data from that system are used to improve AI models about the system, those models are redeployed, and evaluated in that system. In this talk, Jeff Leek will discuss efforts to build AI engines for cancer both at the Fred Hutch and at national scale. He will highlight the potential impact of building an AI engine by showing some results from an AI model that can be used to generate gene expression data from experimental design descriptions of those experiments. Dr. Leek will connect these ideas back to one of the grand challenges in modern statistics – how do we do inference when the “data” are generated from a model? He will describe the initial efforts toward “inference with predicted data” . This is joint work with many people at Fred Hutch, Synthesize Bio, Johns Hopkins, Memorial Sloan Kettering, Dana Farber, and at UW statistics.
About Jeff Leek, PhD
Dr. Jeff Leek is vice president and chief data officer of Fred Hutch. In these roles, he leads efforts to shape and implement Fred Hutch's integrated data science enterprise, and fosters partnerships within the Seattle area's data science and technology ecosystem. His goal is for Hutch researchers to be able to access field-leading computational resources to advance their science. He also works with faculty to create tools and services that help the Hutch better collect, manage, use and share data, As a biostatistician, Leek develops statistical methods, software, and data resources and analyses that help researchers make sense of massive-scale genomic and biomedical data. As an educational leader, Leek has helped craft online open courses in data science that have enrolled millions. He has also partnered with community-based nonprofits to use data science education for economic and public health development.
Add to Calendar2026-01-15 20:00:002026-01-15 21:00:00AI Seminar Series - Jeff Leek
January Seminar: Jeff Leek, PhD - Building and using AI engines – what do we do when we’ve machine learned everything?
Thursday, January 15, 2026
12-1 p.m
Hybrid: In-person at Mission Hall, MH-1406 or Zoom
Register here
An AI engine is a system where one collects data from a system, the data from that system are used to improve AI models about the system, those models are redeployed, and evaluated in that system. In this talk, Jeff Leek will discuss efforts to build AI engines for cancer both at the Fred Hutch and at national scale. He will highlight the potential impact of building an AI engine by showing some results from an AI model that can be used to generate gene expression data from experimental design descriptions of those experiments. Dr. Leek will connect these ideas back to one of the grand challenges in modern statistics – how do we do inference when the “data” are generated from a model? He will describe the initial efforts toward “inference with predicted data” . This is joint work with many people at Fred Hutch, Synthesize Bio, Johns Hopkins, Memorial Sloan Kettering, Dana Farber, and at UW statistics.
About Jeff Leek, PhD
Dr. Jeff Leek is vice president and chief data officer of Fred Hutch. In these roles, he leads efforts to shape and implement Fred Hutch's integrated data science enterprise, and fosters partnerships within the Seattle area's data science and technology ecosystem. His goal is for Hutch researchers to be able to access field-leading computational resources to advance their science. He also works with faculty to create tools and services that help the Hutch better collect, manage, use and share data, As a biostatistician, Leek develops statistical methods, software, and data resources and analyses that help researchers make sense of massive-scale genomic and biomedical data. As an educational leader, Leek has helped craft online open courses in data science that have enrolled millions. He has also partnered with community-based nonprofits to use data science education for economic and public health development.
Division of Clinical Informatics and Digital TransformationAmerica/Los_Angelespublic